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ai-content-maker/.venv/Lib/site-packages/matplotlib/tests/test_simplification.py

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first commit
2024-05-03 04:18:51 +03:00
import base64
import io
import numpy as np
from numpy.testing import assert_array_almost_equal, assert_array_equal
import pytest
from matplotlib.testing.decorators import (
check_figures_equal, image_comparison, remove_ticks_and_titles)
import matplotlib.pyplot as plt
from matplotlib import patches, transforms
from matplotlib.path import Path
# NOTE: All of these tests assume that path.simplify is set to True
# (the default)
@image_comparison(['clipping'], remove_text=True)
def test_clipping():
t = np.arange(0.0, 2.0, 0.01)
s = np.sin(2*np.pi*t)
fig, ax = plt.subplots()
ax.plot(t, s, linewidth=1.0)
ax.set_ylim((-0.20, -0.28))
@image_comparison(['overflow'], remove_text=True)
def test_overflow():
x = np.array([1.0, 2.0, 3.0, 2.0e5])
y = np.arange(len(x))
fig, ax = plt.subplots()
ax.plot(x, y)
ax.set_xlim(2, 6)
@image_comparison(['clipping_diamond'], remove_text=True)
def test_diamond():
x = np.array([0.0, 1.0, 0.0, -1.0, 0.0])
y = np.array([1.0, 0.0, -1.0, 0.0, 1.0])
fig, ax = plt.subplots()
ax.plot(x, y)
ax.set_xlim(-0.6, 0.6)
ax.set_ylim(-0.6, 0.6)
def test_clipping_out_of_bounds():
# Should work on a Path *without* codes.
path = Path([(0, 0), (1, 2), (2, 1)])
simplified = path.cleaned(clip=(10, 10, 20, 20))
assert_array_equal(simplified.vertices, [(0, 0)])
assert simplified.codes == [Path.STOP]
# Should work on a Path *with* codes, and no curves.
path = Path([(0, 0), (1, 2), (2, 1)],
[Path.MOVETO, Path.LINETO, Path.LINETO])
simplified = path.cleaned(clip=(10, 10, 20, 20))
assert_array_equal(simplified.vertices, [(0, 0)])
assert simplified.codes == [Path.STOP]
# A Path with curves does not do any clipping yet.
path = Path([(0, 0), (1, 2), (2, 3)],
[Path.MOVETO, Path.CURVE3, Path.CURVE3])
simplified = path.cleaned()
simplified_clipped = path.cleaned(clip=(10, 10, 20, 20))
assert_array_equal(simplified.vertices, simplified_clipped.vertices)
assert_array_equal(simplified.codes, simplified_clipped.codes)
def test_noise():
np.random.seed(0)
x = np.random.uniform(size=50000) * 50
fig, ax = plt.subplots()
p1 = ax.plot(x, solid_joinstyle='round', linewidth=2.0)
# Ensure that the path's transform takes the new axes limits into account.
fig.canvas.draw()
path = p1[0].get_path()
transform = p1[0].get_transform()
path = transform.transform_path(path)
simplified = path.cleaned(simplify=True)
assert simplified.vertices.size == 25512
def test_antiparallel_simplification():
def _get_simplified(x, y):
fig, ax = plt.subplots()
p1 = ax.plot(x, y)
path = p1[0].get_path()
transform = p1[0].get_transform()
path = transform.transform_path(path)
simplified = path.cleaned(simplify=True)
simplified = transform.inverted().transform_path(simplified)
return simplified
# test ending on a maximum
x = [0, 0, 0, 0, 0, 1]
y = [.5, 1, -1, 1, 2, .5]
simplified = _get_simplified(x, y)
assert_array_almost_equal([[0., 0.5],
[0., -1.],
[0., 2.],
[1., 0.5]],
simplified.vertices[:-2, :])
# test ending on a minimum
x = [0, 0, 0, 0, 0, 1]
y = [.5, 1, -1, 1, -2, .5]
simplified = _get_simplified(x, y)
assert_array_almost_equal([[0., 0.5],
[0., 1.],
[0., -2.],
[1., 0.5]],
simplified.vertices[:-2, :])
# test ending in between
x = [0, 0, 0, 0, 0, 1]
y = [.5, 1, -1, 1, 0, .5]
simplified = _get_simplified(x, y)
assert_array_almost_equal([[0., 0.5],
[0., 1.],
[0., -1.],
[0., 0.],
[1., 0.5]],
simplified.vertices[:-2, :])
# test no anti-parallel ending at max
x = [0, 0, 0, 0, 0, 1]
y = [.5, 1, 2, 1, 3, .5]
simplified = _get_simplified(x, y)
assert_array_almost_equal([[0., 0.5],
[0., 3.],
[1., 0.5]],
simplified.vertices[:-2, :])
# test no anti-parallel ending in middle
x = [0, 0, 0, 0, 0, 1]
y = [.5, 1, 2, 1, 1, .5]
simplified = _get_simplified(x, y)
assert_array_almost_equal([[0., 0.5],
[0., 2.],
[0., 1.],
[1., 0.5]],
simplified.vertices[:-2, :])
# Only consider angles in 0 <= angle <= pi/2, otherwise
# using min/max will get the expected results out of order:
# min/max for simplification code depends on original vector,
# and if angle is outside above range then simplification
# min/max will be opposite from actual min/max.
@pytest.mark.parametrize('angle', [0, np.pi/4, np.pi/3, np.pi/2])
@pytest.mark.parametrize('offset', [0, .5])
def test_angled_antiparallel(angle, offset):
scale = 5
np.random.seed(19680801)
# get 15 random offsets
# TODO: guarantee offset > 0 results in some offsets < 0
vert_offsets = (np.random.rand(15) - offset) * scale
# always start at 0 so rotation makes sense
vert_offsets[0] = 0
# always take the first step the same direction
vert_offsets[1] = 1
# compute points along a diagonal line
x = np.sin(angle) * vert_offsets
y = np.cos(angle) * vert_offsets
# will check these later
x_max = x[1:].max()
x_min = x[1:].min()
y_max = y[1:].max()
y_min = y[1:].min()
if offset > 0:
p_expected = Path([[0, 0],
[x_max, y_max],
[x_min, y_min],
[x[-1], y[-1]],
[0, 0]],
codes=[1, 2, 2, 2, 0])
else:
p_expected = Path([[0, 0],
[x_max, y_max],
[x[-1], y[-1]],
[0, 0]],
codes=[1, 2, 2, 0])
p = Path(np.vstack([x, y]).T)
p2 = p.cleaned(simplify=True)
assert_array_almost_equal(p_expected.vertices,
p2.vertices)
assert_array_equal(p_expected.codes, p2.codes)
def test_sine_plus_noise():
np.random.seed(0)
x = (np.sin(np.linspace(0, np.pi * 2.0, 50000)) +
np.random.uniform(size=50000) * 0.01)
fig, ax = plt.subplots()
p1 = ax.plot(x, solid_joinstyle='round', linewidth=2.0)
# Ensure that the path's transform takes the new axes limits into account.
fig.canvas.draw()
path = p1[0].get_path()
transform = p1[0].get_transform()
path = transform.transform_path(path)
simplified = path.cleaned(simplify=True)
assert simplified.vertices.size == 25240
@image_comparison(['simplify_curve'], remove_text=True, tol=0.017)
def test_simplify_curve():
pp1 = patches.PathPatch(
Path([(0, 0), (1, 0), (1, 1), (np.nan, 1), (0, 0), (2, 0), (2, 2),
(0, 0)],
[Path.MOVETO, Path.CURVE3, Path.CURVE3, Path.CURVE3, Path.CURVE3,
Path.CURVE3, Path.CURVE3, Path.CLOSEPOLY]),
fc="none")
fig, ax = plt.subplots()
ax.add_patch(pp1)
ax.set_xlim((0, 2))
ax.set_ylim((0, 2))
@check_figures_equal()
def test_closed_path_nan_removal(fig_test, fig_ref):
ax_test = fig_test.subplots(2, 2).flatten()
ax_ref = fig_ref.subplots(2, 2).flatten()
# NaN on the first point also removes the last point, because it's closed.
path = Path(
[[-3, np.nan], [3, -3], [3, 3], [-3, 3], [-3, -3]],
[Path.MOVETO, Path.LINETO, Path.LINETO, Path.LINETO, Path.CLOSEPOLY])
ax_test[0].add_patch(patches.PathPatch(path, facecolor='none'))
path = Path(
[[-3, np.nan], [3, -3], [3, 3], [-3, 3], [-3, np.nan]],
[Path.MOVETO, Path.LINETO, Path.LINETO, Path.LINETO, Path.LINETO])
ax_ref[0].add_patch(patches.PathPatch(path, facecolor='none'))
# NaN on second-last point should not re-close.
path = Path(
[[-2, -2], [2, -2], [2, 2], [-2, np.nan], [-2, -2]],
[Path.MOVETO, Path.LINETO, Path.LINETO, Path.LINETO, Path.CLOSEPOLY])
ax_test[0].add_patch(patches.PathPatch(path, facecolor='none'))
path = Path(
[[-2, -2], [2, -2], [2, 2], [-2, np.nan], [-2, -2]],
[Path.MOVETO, Path.LINETO, Path.LINETO, Path.LINETO, Path.LINETO])
ax_ref[0].add_patch(patches.PathPatch(path, facecolor='none'))
# Test multiple loops in a single path (with same paths as above).
path = Path(
[[-3, np.nan], [3, -3], [3, 3], [-3, 3], [-3, -3],
[-2, -2], [2, -2], [2, 2], [-2, np.nan], [-2, -2]],
[Path.MOVETO, Path.LINETO, Path.LINETO, Path.LINETO, Path.CLOSEPOLY,
Path.MOVETO, Path.LINETO, Path.LINETO, Path.LINETO, Path.CLOSEPOLY])
ax_test[1].add_patch(patches.PathPatch(path, facecolor='none'))
path = Path(
[[-3, np.nan], [3, -3], [3, 3], [-3, 3], [-3, np.nan],
[-2, -2], [2, -2], [2, 2], [-2, np.nan], [-2, -2]],
[Path.MOVETO, Path.LINETO, Path.LINETO, Path.LINETO, Path.LINETO,
Path.MOVETO, Path.LINETO, Path.LINETO, Path.LINETO, Path.LINETO])
ax_ref[1].add_patch(patches.PathPatch(path, facecolor='none'))
# NaN in first point of CURVE3 should not re-close, and hide entire curve.
path = Path(
[[-1, -1], [1, -1], [1, np.nan], [0, 1], [-1, 1], [-1, -1]],
[Path.MOVETO, Path.LINETO, Path.CURVE3, Path.CURVE3, Path.LINETO,
Path.CLOSEPOLY])
ax_test[2].add_patch(patches.PathPatch(path, facecolor='none'))
path = Path(
[[-1, -1], [1, -1], [1, np.nan], [0, 1], [-1, 1], [-1, -1]],
[Path.MOVETO, Path.LINETO, Path.CURVE3, Path.CURVE3, Path.LINETO,
Path.CLOSEPOLY])
ax_ref[2].add_patch(patches.PathPatch(path, facecolor='none'))
# NaN in second point of CURVE3 should not re-close, and hide entire curve
# plus next line segment.
path = Path(
[[-3, -3], [3, -3], [3, 0], [0, np.nan], [-3, 3], [-3, -3]],
[Path.MOVETO, Path.LINETO, Path.CURVE3, Path.CURVE3, Path.LINETO,
Path.LINETO])
ax_test[2].add_patch(patches.PathPatch(path, facecolor='none'))
path = Path(
[[-3, -3], [3, -3], [3, 0], [0, np.nan], [-3, 3], [-3, -3]],
[Path.MOVETO, Path.LINETO, Path.CURVE3, Path.CURVE3, Path.LINETO,
Path.LINETO])
ax_ref[2].add_patch(patches.PathPatch(path, facecolor='none'))
# NaN in first point of CURVE4 should not re-close, and hide entire curve.
path = Path(
[[-1, -1], [1, -1], [1, np.nan], [0, 0], [0, 1], [-1, 1], [-1, -1]],
[Path.MOVETO, Path.LINETO, Path.CURVE4, Path.CURVE4, Path.CURVE4,
Path.LINETO, Path.CLOSEPOLY])
ax_test[3].add_patch(patches.PathPatch(path, facecolor='none'))
path = Path(
[[-1, -1], [1, -1], [1, np.nan], [0, 0], [0, 1], [-1, 1], [-1, -1]],
[Path.MOVETO, Path.LINETO, Path.CURVE4, Path.CURVE4, Path.CURVE4,
Path.LINETO, Path.CLOSEPOLY])
ax_ref[3].add_patch(patches.PathPatch(path, facecolor='none'))
# NaN in second point of CURVE4 should not re-close, and hide entire curve.
path = Path(
[[-2, -2], [2, -2], [2, 0], [0, np.nan], [0, 2], [-2, 2], [-2, -2]],
[Path.MOVETO, Path.LINETO, Path.CURVE4, Path.CURVE4, Path.CURVE4,
Path.LINETO, Path.LINETO])
ax_test[3].add_patch(patches.PathPatch(path, facecolor='none'))
path = Path(
[[-2, -2], [2, -2], [2, 0], [0, np.nan], [0, 2], [-2, 2], [-2, -2]],
[Path.MOVETO, Path.LINETO, Path.CURVE4, Path.CURVE4, Path.CURVE4,
Path.LINETO, Path.LINETO])
ax_ref[3].add_patch(patches.PathPatch(path, facecolor='none'))
# NaN in third point of CURVE4 should not re-close, and hide entire curve
# plus next line segment.
path = Path(
[[-3, -3], [3, -3], [3, 0], [0, 0], [0, np.nan], [-3, 3], [-3, -3]],
[Path.MOVETO, Path.LINETO, Path.CURVE4, Path.CURVE4, Path.CURVE4,
Path.LINETO, Path.LINETO])
ax_test[3].add_patch(patches.PathPatch(path, facecolor='none'))
path = Path(
[[-3, -3], [3, -3], [3, 0], [0, 0], [0, np.nan], [-3, 3], [-3, -3]],
[Path.MOVETO, Path.LINETO, Path.CURVE4, Path.CURVE4, Path.CURVE4,
Path.LINETO, Path.LINETO])
ax_ref[3].add_patch(patches.PathPatch(path, facecolor='none'))
# Keep everything clean.
for ax in [*ax_test.flat, *ax_ref.flat]:
ax.set(xlim=(-3.5, 3.5), ylim=(-3.5, 3.5))
remove_ticks_and_titles(fig_test)
remove_ticks_and_titles(fig_ref)
@check_figures_equal()
def test_closed_path_clipping(fig_test, fig_ref):
vertices = []
for roll in range(8):
offset = 0.1 * roll + 0.1
# A U-like pattern.
pattern = [
[-0.5, 1.5], [-0.5, -0.5], [1.5, -0.5], [1.5, 1.5], # Outer square
# With a notch in the top.
[1 - offset / 2, 1.5], [1 - offset / 2, offset],
[offset / 2, offset], [offset / 2, 1.5],
]
# Place the initial/final point anywhere in/out of the clipping area.
pattern = np.roll(pattern, roll, axis=0)
pattern = np.concatenate((pattern, pattern[:1, :]))
vertices.append(pattern)
# Multiple subpaths are used here to ensure they aren't broken by closed
# loop clipping.
codes = np.full(len(vertices[0]), Path.LINETO)
codes[0] = Path.MOVETO
codes[-1] = Path.CLOSEPOLY
codes = np.tile(codes, len(vertices))
vertices = np.concatenate(vertices)
fig_test.set_size_inches((5, 5))
path = Path(vertices, codes)
fig_test.add_artist(patches.PathPatch(path, facecolor='none'))
# For reference, we draw the same thing, but unclosed by using a line to
# the last point only.
fig_ref.set_size_inches((5, 5))
codes = codes.copy()
codes[codes == Path.CLOSEPOLY] = Path.LINETO
path = Path(vertices, codes)
fig_ref.add_artist(patches.PathPatch(path, facecolor='none'))
@image_comparison(['hatch_simplify'], remove_text=True)
def test_hatch():
fig, ax = plt.subplots()
ax.add_patch(plt.Rectangle((0, 0), 1, 1, fill=False, hatch="/"))
ax.set_xlim((0.45, 0.55))
ax.set_ylim((0.45, 0.55))
@image_comparison(['fft_peaks'], remove_text=True)
def test_fft_peaks():
fig, ax = plt.subplots()
t = np.arange(65536)
p1 = ax.plot(abs(np.fft.fft(np.sin(2*np.pi*.01*t)*np.blackman(len(t)))))
# Ensure that the path's transform takes the new axes limits into account.
fig.canvas.draw()
path = p1[0].get_path()
transform = p1[0].get_transform()
path = transform.transform_path(path)
simplified = path.cleaned(simplify=True)
assert simplified.vertices.size == 36
def test_start_with_moveto():
# Should be entirely clipped away to a single MOVETO
data = b"""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"""
verts = np.frombuffer(base64.decodebytes(data), dtype='<i4')
verts = verts.reshape((len(verts) // 2, 2))
path = Path(verts)
segs = path.iter_segments(transforms.IdentityTransform(),
clip=(0.0, 0.0, 100.0, 100.0))
segs = list(segs)
assert len(segs) == 1
assert segs[0][1] == Path.MOVETO
def test_throw_rendering_complexity_exceeded():
plt.rcParams['path.simplify'] = False
xx = np.arange(2_000_000)
yy = np.random.rand(2_000_000)
yy[1000] = np.nan
fig, ax = plt.subplots()
ax.plot(xx, yy)
with pytest.raises(OverflowError):
fig.savefig(io.BytesIO())
@image_comparison(['clipper_edge'], remove_text=True)
def test_clipper():
dat = (0, 1, 0, 2, 0, 3, 0, 4, 0, 5)
fig = plt.figure(figsize=(2, 1))
fig.subplots_adjust(left=0, bottom=0, wspace=0, hspace=0)
ax = fig.add_axes((0, 0, 1.0, 1.0), ylim=(0, 5), autoscale_on=False)
ax.plot(dat)
ax.xaxis.set_major_locator(plt.MultipleLocator(1))
ax.yaxis.set_major_locator(plt.MultipleLocator(1))
ax.xaxis.set_ticks_position('bottom')
ax.yaxis.set_ticks_position('left')
ax.set_xlim(5, 9)
@image_comparison(['para_equal_perp'], remove_text=True)
def test_para_equal_perp():
x = np.array([0, 1, 2, 1, 0, -1, 0, 1] + [1] * 128)
y = np.array([1, 1, 2, 1, 0, -1, 0, 0] + [0] * 128)
fig, ax = plt.subplots()
ax.plot(x + 1, y + 1)
ax.plot(x + 1, y + 1, 'ro')
@image_comparison(['clipping_with_nans'])
def test_clipping_with_nans():
x = np.linspace(0, 3.14 * 2, 3000)
y = np.sin(x)
x[::100] = np.nan
fig, ax = plt.subplots()
ax.plot(x, y)
ax.set_ylim(-0.25, 0.25)
def test_clipping_full():
p = Path([[1e30, 1e30]] * 5)
simplified = list(p.iter_segments(clip=[0, 0, 100, 100]))
assert simplified == []
p = Path([[50, 40], [75, 65]], [1, 2])
simplified = list(p.iter_segments(clip=[0, 0, 100, 100]))
assert ([(list(x), y) for x, y in simplified] ==
[([50, 40], 1), ([75, 65], 2)])
p = Path([[50, 40]], [1])
simplified = list(p.iter_segments(clip=[0, 0, 100, 100]))
assert ([(list(x), y) for x, y in simplified] ==
[([50, 40], 1)])